1. Field of the Invention
The present invention relates to the loading of digital music onto personal computers (PCs) and/or portable music players from one or more song databases residing on one or more Internet (or network) servers. More particularly, the present invention relates to the generation and use of a song database(s), where each song is individually categorized based upon predetermined criteria. Consumers may then access the song database(s), and download one or more complete song libraries based upon consumer preference. Since entire song libraries may be downloaded to the PC with, for example, a one or two-click Internet interface and then loaded to the consumer's portable music player (such as an iPod™, an MP3 player, a cellular telephone, a laptop computer, a personal digital assistant (PDA), etc.), it is very quick and easy, as opposed to the current system whereby the consumer must spend hours on his/her computer selecting each song or album or playlist to be loaded onto his/her portable music player. The downloaded library or libraries allow the consumer to generate and listen to playlists, in the well known fashion on his/her PC. The consumer can then side load to his/her portable device: (i) playlists he/she generates on his/her PC, (ii) predetermined playlists recommended by the provider, or (iii) the entire song library. In a preferred embodiment, each song stored on the song database(s) is individually predetermined (pre-categorized) in accordance with five criteria (in addition to the known criteria of artist, album, and song title.)
2. Related Art
With the advent of digital music technology, and especially the MP3 files and the iPod™, consumers now enjoy access to approximately 4,000,000 song choices. On-line music download services such as Apple iTunes™ and on-line subscription-based services such as Napster, Rhapsody, and MTV/Urge provide over 2,700,000 songs that consumers can utilize to listen to, buy, or discover new music.
This tidal wave of choices has created a need for consumers to filter and select music in order to discover new music as well as organize the music they are already familiar with. One method of organizing this universe is to create playlists of songs. This allows consumers to avoid the need to individually select songs by artist, song, or album name each time they want to listen.
In order to enjoy a playlist of songs, consumers currently have two general choices. First, they can select a live radio broadcast station that is programmed for a particular style of preferred music. Today, such platforms include Internet radio, pod-casting, satellite, terrestrial and cable-based music broadcasters. Listening to live broadcast requires no expertise or time on the listeners' part to enjoy hundreds of different station playlist options. The music is selected for them by professional programmers to fit a particular “format” or theme. However, listening to playlists on these broadcast platforms has certain significant limitations. First, with a few minor exceptions, broadcast songs cannot be stored on the personal computer (PC) or portable music player because they are licensed for “listen only” consumption. This means consumers cannot fast-forward over songs they do not like (as they can with songs stored on a portable MP3 player or CD player). Instead, to listen to music they like, the consumers must station-surf, which is especially annoying while driving a car or while exercising. Second, the number of choices available from such satellite, cable, or terrestrial broadcast platforms is small and limited in depth, including the number of new artists and genres covered. Third, the number of commercial-free stations is extremely limited, with Sirius and XM offering only 69 channels each. And, these supposedly commercial-free stations are actually full of house ads promoting the broadcasters own service offerings. This too eliminates the feel of listening to one's personal library of songs without interruption. Fourth, Internet Radio is a “listen-only” format so songs cannot be legally stored on the PC or portable device.
To enjoy a desired playlist of songs, the consumers' second general option is to take the time to search for individual songs (or entire playlists) on their own, and then download them, one at a time, into their personal libraries or set of playlists. Each such do-it-yourself library can then be stored on a PC or portable MP3 player, thus allowing the consumer to skip to the next song without limitation.
Over the last several years, dozens of techniques have been developed to assist these do-it-yourself consumers in creating their own playlists from the millions of songs now available to them. These methods typically make the same two assumptions regarding music consumers: 1) The consumers want to be actively involved in choosing songs for a personalized station playlist. More specifically, it is assumed that computer-savvy music listeners with high-speed Internet access and MP3 player devices have the expertise and the time to spend many hours attempting to “discover” and download desirable music; and 2) Each consumer wants to select among a narrow range of songs and artists that they are familiar with, in order to create a profile of song traits or user preferences that can be used to sort through a 4,000,000 song universe, to recommend songs for download. The idea is to narrow the songs available to conform to past listening habits. This ignores the possible discovery of high quality new music from unfamiliar sources.
As it turns out, none of these do-it-yourself or “active” methods have appealed to a mass audience. In fact, the average owner of an iPod™ or similar MP3 player device has only two to three hundred songs stored, and purchases less than one new song per month, on average. Likewise, all eight of the music subscription services now available have collectively only obtained a total of roughly 2.0 million subscribers. None of these systems are enjoying significant growth, despite the fact that over 90 million Americans now have iPods™ or similar MP3 player devices. The reason for this is pretty simple: The vast majority of music listeners do not have the time, the expertise, or the desire to sort through the vast universe of available songs—it is simply too much work. Furthermore, the systems and methods now available to recommend songs, based on various inputs and preferences from the user, are ineffective and are also too much work. Finally, because they are based on a consumer's past, and usually highly limited, experience with the music universe, they limit the chance to discover music from unfamiliar genres, sources, artists, or time periods, and enjoy the kind of diversity now available.
These active or user-based playlist recommendation systems fall into five broad categories:
Song Matching Algorithms: The user is asked to provide favorite songs that are then analyzed in detail to find songs with similar “musical DNA” (e.g., Pandora, Yahoo-Music Match and Alcalde et. al., U.S. Pat. No. 7,081,579).
Playlist Sharing The user shares his playlists with others to get ideas from people with similar tastes (e.g., mystrands.com, last.fm.com, MOG.com).
Artist Matching Systems: Instead of favorite songs, the user inputs favorite artists or radio stations to generate a list of recommended songs (e.g., Porteus et al., U.S. Pat. No. 6,933,433).
Identifying a “Plurality” of Preferences: The user fills out a complicated survey of “desired and undesirable seed items,” that is then used to recommend songs (e.g. Platt, U.S. Pat. No. 6,987,221).
Genre/Station Preferences: A user's radio station/genre choices form the basis for recommending songs (Doshida et al., U.S. Patent Application Publication No. 20040193649).
Again, all of these systems assume that: 1) the listener wants his/her past choices to limit his/her future choices; and 2) the listener has the time to be actively involved in the process of generating playlists.
Meanwhile, new passive systems for retrieving and listening to playlists that are prepared by professional programmers have had fantastic success. Such “passive” systems include Internet radio broadcasters with an online listening audience of approximately 60,000,000 people, and subscription-based satellite radio services, currently with approximately 10,000,000 subscribers. Both of these types of systems are presently growing at an approximate rate of 25% annually. The present invention is intended to address this need for passive systems and methods for providing song playlists to consumers that can be legally stored on their PC or portable device thereby avoiding the limitations of live broadcast.